Triple
T33509417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferret Face |
E858198
|
entity |
| Predicate | characterRankContext |
P197333
|
FINISHED |
| Object | Major |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Major | Statement: [Ferret Face, characterRankContext, Major]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRankContext Context triple: [Ferret Face, characterRankContext, Major]
-
A.
rankingRole
Indicates that one entity holds a specific position or level in an ordered hierarchy or ranking relative to others.
-
B.
rankInformation
Indicates that information is being ordered or prioritized according to some ranking criteria or relevance.
-
C.
portrayedRankOfCharacter
chosen
Indicates the military or hierarchical rank that a character is depicted as holding within a given portrayal or work.
-
D.
chronRank
Indicates the relative chronological order or ranking of events or time-related entities with respect to one another.
-
E.
rankSignificance
Indicates how important or influential one entity is relative to others within a specified context or ordering.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff3fb2318c81908a46c2f513608935 |
completed | May 9, 2026, 2:07 p.m. |
| PD | Predicate disambiguation | batch_69ff3e96dcc48190819f6204680d84aa |
completed | May 9, 2026, 2:03 p.m. |
Created at: May 1, 2026, 1:38 a.m.